code: def forward(self, x):
      for lin, batch_norm in zip(self.lins[:-1], self.batch_norms):
          x = lin(x)
          if self.relu_last:
              x = batch_norm(x).relu_()
          else:
              x = batch_norm(x.relu_())
          x = F.dropout(x, p=self.dropout, training=self.training)
      x = self.lins[-1](x)
      return x
  
file_path: ogb/examples/lsc/mag240m/preprocess_correct_and_smooth.py
imports: import time
  import argparse
  from tqdm.auto import tqdm
  import torch
  import numpy
  import torch.nn.functional
  from torch.utils.data import DataLoader
  from torch.nn import ModuleList, Linear, BatchNorm1d, Identity
  from ogb.utils.url import makedirs
  from ogb.lsc import MAG240MDataset, MAG240MEvaluator
  from root import ROOT
label_desc: Use image node_id 3 for calling the MLP obj's underlying member method code with example usage: obj.forward(x) and returns: x